This dataset was collected by Shan-Hung Wu and DataLab members at National Tsing Hua University, Taiwan. It random sampled 180 images from the NUS-WIDE image database. Each image has 500 features consisting of the bag of words based on SIFT descriptions. With a series of experiments on the Amazon Mechanical Turk platform, there are 325 user-perceived clusters from 100 users and their corresponding descriptions.

- data_feature.csv : 180 images x 500 features
- Each row is 500 features vector consisting of the bag of words based on SIFT descriptions. All 180 images are sampled from NUS-WIDE dataset.
- Reference: [Web Link]

- supervision_cluster_matrix.csv : 108 bag of words x 183 clusters
- We parse the raw supervisions and merge similar words into 108 dimensions. Each row is a description of corresponding cluster.

- cluster_list.csv:
-FileName: ['UserId'], ['ImageId Cluster'], ['Description']
-['UserId']: Specify the user who created the cluster.
-['ImageId Cluster']: Image ids in the cluster which are separated by ';'.
-['Description']: A sentence or some keywords describe the images in the cluster by user.
- 325 records(clusters) in total.